Research Article
Modeling Desire for More Children Among Childbearing Women in Ethiopia: Application of a Generalized Estimating Equation
Kassu Mehari Beyene*
,
Sara Abera Bekele,
Shiferaw Gedefa Fentie
Issue:
Volume 11, Issue 3, September 2026
Pages:
65-73
Received:
30 March 2026
Accepted:
1 June 2026
Published:
17 September 2026
Abstract: It is well documented that high fertility rates can have an adverse effect on the health of women and children, especially in developing countries that lack health infrastructure. The fertility rate in Ethiopia is one of the highest in the world. In 2019 the estimated total fertility rate is 4.15 births per woman. Although, the total fertility rate of the country is far above the acceptable level, many married women want to have another child. In 2016 it is estimated that fifty-six percent of currently married women age 15-49 want to have another child. The main objective of this study is to model desire for more children among childbearing women using longitudinal approaches as well as to evaluate the determinant factors for the desire for more children among childbearing women in Ethiopia. The source of data for this study is the 2016 Ethiopian Demographic and Health Survey (EDHS) which was a nationally representative survey of women in the age group 15-49 years. Data about desire for more children among childbearing women will be analysed. The statistical method used to analyze the data is a marginal longitudinal model, specifically the generalized estimating equation (GEE). The generalized estimating equations analysis revealed that the desire for more children was significantly higher among women aged 15-44 (specifically in the groups 15-19, 20-24, 25-29, 30-34, 35-39, and 40-44), women with 0-3 and 4-5 living children, and women not using contraceptives, compared to their counterparts. Conversely, the desire for more children was significantly lower among women with no, and primary education; women with 0-3 and 4-5 ideal number of children; and women residing in the Amhara, Southern Nations, Nationalities and Peoples Region (SNNPR), Oromia, Benishangul, Addis Ababa, Gambela, Tigray, Dire Dawa, and Harari regions, compared to their counterparts. The results revealed that the desire for more children generally increases with education level and ideal number of children. Conversely, women using contraceptives desire fewer children compared to those not using them. Therefore, federal and regional governments need to implement significant interventions to reduce fertility desire. Additionally, non-governmental organizations and civil societies can raise crucial awareness about the benefits of reduced fertility desire, especially among young women, women with no education, women with a high ideal number of children, women with fewer living children, and women who do not use contraceptives.
Abstract: It is well documented that high fertility rates can have an adverse effect on the health of women and children, especially in developing countries that lack health infrastructure. The fertility rate in Ethiopia is one of the highest in the world. In 2019 the estimated total fertility rate is 4.15 births per woman. Although, the total fertility rate...
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Research Article
Association Structures in Bayesian Joint Models of Longitudinal Markers and Survival Outcomes: Application to Cardiac Data
Tayu Nigusie Abebe*
Issue:
Volume 11, Issue 3, September 2026
Pages:
74-85
Received:
1 August 2026
Accepted:
4 September 2026
Published:
20 September 2026
Abstract: In clinical research, longitudinal biomarkers and time-to-event outcomes are often correlated. Standard separate modeling of these processes leads to biased estimates due to the failure to account for endogeneity. This study investigates the application of the Bayesian joint modeling framework to quantify the association between pulse rate trajectories and mortality risk in cardiac patients. A primary focus is placed on comparing various association structures to determine the most effective parameterization for medical inference. Data from cardiac patients at an Ethiopian cardiac center were analyzed using a linear mixed model for pulse rate and a Cox PH model for time-to-death. Three distinct association structures current value, current value plus slope, and shared random effects were estimated via Markov chain Monte Carlo (MCMC) algorithms. The current value plus slope association structure provided the best model fit, demonstrating that both the current level of pulse rate and its instantaneous rate of change are significant predictors of mortality. Clinical findings also indicated that underweight status and pulmonary complications significantly increase the hazard of death, while corrective surgery serves as a protective factor. Joint modeling offers a robust unified approach for medical research, yielding more efficient and less biased estimates than separate analyses. The choice of association structure is critical; specifically, incorporating the trajectory's slope alongside its current value enhances the predictive performance and interpretability of clinical biomarkers in survival analysis.
Abstract: In clinical research, longitudinal biomarkers and time-to-event outcomes are often correlated. Standard separate modeling of these processes leads to biased estimates due to the failure to account for endogeneity. This study investigates the application of the Bayesian joint modeling framework to quantify the association between pulse rate trajecto...
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